314 lines
7.5 KiB
Python
314 lines
7.5 KiB
Python
import subprocess
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import sys
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from typing import List
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import pytest
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import pandas as pd
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from pandas import api
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import pandas._testing as tm
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class Base:
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def check(self, namespace, expected, ignored=None):
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# see which names are in the namespace, minus optional
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# ignored ones
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# compare vs the expected
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result = sorted(f for f in dir(namespace) if not f.startswith("__"))
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if ignored is not None:
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result = sorted(set(result) - set(ignored))
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expected = sorted(expected)
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tm.assert_almost_equal(result, expected)
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class TestPDApi(Base):
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# these are optionally imported based on testing
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# & need to be ignored
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ignored = ["tests", "locale", "conftest"]
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# top-level sub-packages
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lib = [
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"api",
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"arrays",
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"compat",
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"core",
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"errors",
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"pandas",
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"plotting",
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"test",
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"testing",
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"tseries",
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"util",
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"options",
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"io",
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]
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# these are already deprecated; awaiting removal
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deprecated_modules: List[str] = ["np", "datetime"]
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# misc
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misc = ["IndexSlice", "NaT", "NA"]
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# top-level classes
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classes = [
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"Categorical",
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"CategoricalIndex",
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"DataFrame",
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"DateOffset",
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"DatetimeIndex",
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"ExcelFile",
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"ExcelWriter",
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"Float64Index",
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"Flags",
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"Grouper",
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"HDFStore",
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"Index",
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"Int64Index",
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"MultiIndex",
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"Period",
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"PeriodIndex",
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"RangeIndex",
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"UInt64Index",
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"Series",
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"SparseDtype",
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"StringDtype",
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"Timedelta",
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"TimedeltaIndex",
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"Timestamp",
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"Interval",
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"IntervalIndex",
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"CategoricalDtype",
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"PeriodDtype",
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"IntervalDtype",
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"DatetimeTZDtype",
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"BooleanDtype",
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"Int8Dtype",
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"Int16Dtype",
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"Int32Dtype",
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"Int64Dtype",
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"UInt8Dtype",
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"UInt16Dtype",
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"UInt32Dtype",
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"UInt64Dtype",
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"Float32Dtype",
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"Float64Dtype",
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"NamedAgg",
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]
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# these are already deprecated; awaiting removal
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deprecated_classes: List[str] = []
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# these should be deprecated in the future
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deprecated_classes_in_future: List[str] = ["SparseArray"]
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# external modules exposed in pandas namespace
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modules: List[str] = []
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# top-level functions
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funcs = [
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"array",
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"bdate_range",
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"concat",
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"crosstab",
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"cut",
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"date_range",
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"interval_range",
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"eval",
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"factorize",
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"get_dummies",
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"infer_freq",
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"isna",
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"isnull",
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"lreshape",
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"melt",
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"notna",
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"notnull",
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"offsets",
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"merge",
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"merge_ordered",
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"merge_asof",
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"period_range",
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"pivot",
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"pivot_table",
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"qcut",
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"show_versions",
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"timedelta_range",
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"unique",
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"value_counts",
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"wide_to_long",
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]
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# top-level option funcs
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funcs_option = [
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"reset_option",
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"describe_option",
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"get_option",
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"option_context",
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"set_option",
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"set_eng_float_format",
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]
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# top-level read_* funcs
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funcs_read = [
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"read_clipboard",
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"read_csv",
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"read_excel",
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"read_fwf",
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"read_gbq",
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"read_hdf",
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"read_html",
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"read_json",
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"read_pickle",
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"read_sas",
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"read_sql",
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"read_sql_query",
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"read_sql_table",
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"read_stata",
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"read_table",
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"read_feather",
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"read_parquet",
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"read_orc",
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"read_spss",
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]
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# top-level json funcs
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funcs_json = ["json_normalize"]
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# top-level to_* funcs
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funcs_to = ["to_datetime", "to_numeric", "to_pickle", "to_timedelta"]
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# top-level to deprecate in the future
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deprecated_funcs_in_future: List[str] = []
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# these are already deprecated; awaiting removal
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deprecated_funcs: List[str] = []
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# private modules in pandas namespace
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private_modules = [
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"_config",
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"_hashtable",
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"_lib",
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"_libs",
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"_np_version_under1p17",
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"_np_version_under1p18",
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"_is_numpy_dev",
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"_testing",
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"_tslib",
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"_typing",
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"_version",
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]
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def test_api(self):
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checkthese = (
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self.lib
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+ self.misc
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+ self.modules
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+ self.classes
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+ self.funcs
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+ self.funcs_option
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+ self.funcs_read
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+ self.funcs_json
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+ self.funcs_to
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+ self.private_modules
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)
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self.check(pd, checkthese, self.ignored)
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def test_depr(self):
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deprecated_list = (
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self.deprecated_modules
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+ self.deprecated_classes
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+ self.deprecated_classes_in_future
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+ self.deprecated_funcs
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+ self.deprecated_funcs_in_future
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)
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for depr in deprecated_list:
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with tm.assert_produces_warning(FutureWarning):
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_ = getattr(pd, depr)
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def test_datetime():
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from datetime import datetime
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import warnings
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", FutureWarning)
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assert datetime(2015, 1, 2, 0, 0) == pd.datetime(2015, 1, 2, 0, 0)
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assert isinstance(pd.datetime(2015, 1, 2, 0, 0), pd.datetime)
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def test_sparsearray():
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import warnings
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", FutureWarning)
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assert isinstance(pd.array([1, 2, 3], dtype="Sparse"), pd.SparseArray)
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def test_np():
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import warnings
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import numpy as np
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with warnings.catch_warnings():
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warnings.simplefilter("ignore", FutureWarning)
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assert (pd.np.arange(0, 10) == np.arange(0, 10)).all()
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class TestApi(Base):
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allowed = ["types", "extensions", "indexers"]
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def test_api(self):
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self.check(api, self.allowed)
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class TestTesting(Base):
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funcs = [
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"assert_frame_equal",
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"assert_series_equal",
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"assert_index_equal",
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"assert_extension_array_equal",
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]
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def test_testing(self):
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from pandas import testing
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self.check(testing, self.funcs)
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def test_util_testing_deprecated(self):
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# avoid cache state affecting the test
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sys.modules.pop("pandas.util.testing", None)
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with tm.assert_produces_warning(FutureWarning) as m:
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import pandas.util.testing # noqa: F401
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assert "pandas.util.testing is deprecated" in str(m[0].message)
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assert "pandas.testing instead" in str(m[0].message)
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def test_util_testing_deprecated_direct(self):
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# avoid cache state affecting the test
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sys.modules.pop("pandas.util.testing", None)
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with tm.assert_produces_warning(FutureWarning) as m:
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from pandas.util.testing import assert_series_equal # noqa: F401
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assert "pandas.util.testing is deprecated" in str(m[0].message)
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assert "pandas.testing instead" in str(m[0].message)
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def test_util_in_top_level(self):
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# in a subprocess to avoid import caching issues
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out = subprocess.check_output(
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[
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sys.executable,
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"-c",
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"import pandas; pandas.util.testing.assert_series_equal",
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],
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stderr=subprocess.STDOUT,
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).decode()
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assert "pandas.util.testing is deprecated" in out
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with pytest.raises(AttributeError, match="foo"):
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pd.util.foo
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